Table 1 provides a summary of the regression analysis for the variable predicting happiness.What can the researcher say about the variable sense of humor?A)The variable sense of humor does not contribute to the model for predicting happiness.B)The variable sense of humor does contribute to the model for predicting happiness. **Table 1: Summary of Regression Analysis for Variable Predicting Happiness (N = 20)**| Variable | B | SE B | β ||-----------------|-----|------|-----|| Sense of humor | 1.22| .37 | .61*|*Note. *p < .05***Explanation:**This table presents the results of a regression analysis examining the influence of a variable, "Sense of humor," on predicting happiness among 20 participants.- **B (Unstandardized Coefficient):** Indicates the strength and direction of the relationship between the independent variable (sense of humor) and the dependent variable (happiness). A B value of 1.22 suggests a positive association. - **SE B (Standard Error of B):** Measures the precision of the B coefficient. A smaller SE indicates a more precise estimate. Here, it is 0.37.- **β (Beta Coefficient):** A standardized measure of the strength of the relationship, allowing comparison across different variables. The beta of .61, marked with an asterisk (*), indicates a statistically significant relationship with p < .05, meaning there is less than a 5% chance this result is due to random variation. This suggests that a sense of humor is a meaningful predictor of happiness in this study.

Table 1 provides a summary of the regression analysis for the variable predicting happiness. What can the researcher say about the variable sense of humor? A)The variable sense of humor does not contribute to the model for predicting happiness. B)The variable sense of humor does contribute to the model for predicting happiness.

Table 1 provides a summary of the regression analysis for the variable predicting happiness. What can the researcher say about the variable sense of humor? A)The variable sense of humor does not contribute to the model for predicting happiness. B)The variable sense of humor does contribute to the model for predicting happiness.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Which statement is not correct for multiple regression model? When we interpret this categorical variable, we would say the change we observe when one switches from the reference category to the specific category. The reference category will not be displayed in our model results. If we include a categorical variable with more than two values (e.g., religion) as an independent variable, we want to include a dummy variable for all categories except for two. We can include more than two categorical variables in the model. The value of the independent variable not included in the model is called "reference category."
what can go wrong and the caution that needs to be exercised when using regression models.
What are the coefficients of correlation between miles per gallon and horsepower? Between miles per gallon and the weight of the car? What are the directions and strengths of these coefficients? Do the coefficients of correlation indicate a strong correlation, weak correlation, or no correlation between these variables? See Step 4 in the Python script. Write the multiple regression equation for miles per gallon as the response variable. Use weight and horsepower as predictor variables. See Step 5 in the Python script. How might the car rental company use this model?
In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67 the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?